MISUSE DETECTION - A Neural Network vs. A Genetic Algorithm Approach

Pedro A. Diaz-Gomez, Dean F. Hougen

2007

Abstract

Misuse detection can be addressed as an optimization problem, where the problem is to find an array of possible intrusions x that maximizes a function f (·) subject to a constraint r imposed by a user’s actions performed on a computer. This position paper presents and compares two ways of finding x, in audit data, by using neural networks and genetic algorithms.

Paper Citation

in Harvard Style

A. Diaz-Gomez P. and F. Hougen D. (2007). MISUSE DETECTION - A Neural Network vs. A Genetic Algorithm Approach . In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-972-8865-89-4, pages 459-462. DOI: 10.5220/0002410904590462

in Bibtex Style

@conference{iceis07,
author={Pedro A. Diaz-Gomez and Dean F. Hougen},
title={MISUSE DETECTION - A Neural Network vs. A Genetic Algorithm Approach},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2007},
pages={459-462},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002410904590462},
isbn={978-972-8865-89-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - MISUSE DETECTION - A Neural Network vs. A Genetic Algorithm Approach
SN - 978-972-8865-89-4
AU - A. Diaz-Gomez P.
AU - F. Hougen D.
PY - 2007
SP - 459
EP - 462
DO - 10.5220/0002410904590462